How Highlighter can save your life in Tableau

Data Exploration is the first thing we sought out to do when data is granted to us. It’s the process of making ourselves familiar with data, finding the patterns and making out a sense from the information which data has provided to us. No matter how skilled the practitioner might be, for every new problem, one thing is sure that data exploration would be messy and even sometimes bizarre. In this post, we will look at how HIGHLIGHTER in Tableau proves to be a silver line when it comes to data exploration.

We are using Long-term unemployment statistics data from America for this post. This data provides us variables as Age, Gender, Period and the aggregation of unemployed in a given period(month of the year). 

Age has seven categories; Gender has 2, Period is a collection of each month starting from January 2005 to Feburary 2015. 

Long-term unemployment statistics

Month wise Unemployment with Gender and Age

The graph above was the first graph which I made when started data exploration for this data. This messy graph shows month wise unemployment where two different colours are for Gender and different shapes have been used to display different age groups.  Let’s use a highlighter here to segregate the granularity and see information one by one.

Tableau is intelligent enough to read the data and find out the variables which have many categories in them. If you right-click on such particular variable the menu will pop as in above image. Select Show Highlighter to activate it.

As soon the highlighter gets activated it would be displayed on the right side of the graph. See the image below for more. Some people drag it to the left side for the convenience.

As soon you will hover your pointer over the text box of the highlighter, a menu of all the categories that variable has will pop. Select any of the category(you can include and exclude as many categories as you feel fit). 

Through above images its not hard to notice that how helpful Highlighter is. Highlighter will give a relief when you will struggle to make out a meaning of what you have just made. 

About the author

Harsh Bhojwani

Hi, I'm Harsh Bhojwani, an aspiring blogger with an obsession for all things related to Data Science. This blog is dedicated to helping people learn Data Science.

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